We investigate the probable existence of dark matter in the interior of neutron stars. Despite the current state of knowledge, the observational properties of neutron stars have not definitively ruled out the possibility of dark matter. Our research endeavors to shed light on this intriguing mystery by examining how certain neutron star properties, including mass, radius, and tidal deformability, might serve as constraints for the dark matter model. In our investigation, we adopt a two-fluid approach to calculate the properties of neutron stars. For the nuclear matter equation-of-state (EOS), we employ several realistic EOS derived from the relativistic mean field model (RMF), each exhibiting varying stiffness and composition. In parallel, we look into the dark matter EOS, considering fermionic matter with repulsive interaction described by a relativistic mean field Lagrangian. A reasonable range of parameters is sampled meticulously. Our study primarily focuses on exploring correlations between the dark matter model parameters and different neutron star properties using a rich set of EOSs. Interestingly, our results reveal a promising correlation between the dark matter model parameters and stellar properties, particularly when we ignore the uncertainties in the nuclear matter EOS. However, when introducing uncertainties in the nuclear sector, the correlation weakens, suggesting that the task of conclusively constraining any particular dark matter model might be challenging using global properties alone, such as mass, radius, and tidal deformability. Notably, we find that dark-matter admixed stars tend to have higher central baryonic density, potentially allowing for non-nucleonic degrees of freedom or direct Urca processes in stars with lower masses. There is also a tantalizing hint regarding the detection of stars with the same mass but different surface temperatures, which may indicate the presence of dark matter. With our robust and extensive dataset, we delve deeper and demonstrate that even in the presence of dark matter, the semiuniversal C-Love relation remains intact. This captivating finding adds another layer of complexity to the interplay between dark matter and neutron star properties. Published by the American Physical Society 2024

Context. The equation of state (EOS) for neutron stars is modeled using the relativistic mean field (RMF) approach with a mesonic nonlinear (NL) interaction, a modified sigma potential (NL–σ cut) that mimics the effect of an exclusion volume or the onset of a quarkyonic phase, and influences of dark matter in the NL (NL DM). Experimental constraints on the general properties of finite nuclei and heavy ion collisions, as well as astrophysical observations of neutron star radii and tidal deformation are taken into account. Aims. We evaluate the plausibility and implications of each scenario by exploring how modifications to the RMF model, including the NL–σ cut and dark matter influences, affect the neutron star EOS. Additionally, the study examines the tension between the PREX-II experimental data and other constraints, aiming to identify which model is able to optimally reconcile the available experimental and observational evidence. Methods. A Bayesian analysis framework was employed to systematically compare the different EOS scenarios. This approach integrates constraints from nuclear experiments (finite nuclei properties and heavy ion collisions) and astrophysical observations (neutron star radii, tidal deformation, and PSR J0437–4715 measurements) to rigorously assess the viability of each model. Results. The analysis shows that including the PREX–II data renders all models less favorable, indicating significant tension with the other constraints and incompatibility with chiral effective field theory calculations of pure neutron matter. When excluding PREX–II, the NL–σ cut model emerges with the highest Bayes evidence, favoring a stiffening of the EOS at high densities, whereas the model incorporating a dark matter component is the least favorable. Furthermore, new PSR J0437–4715 measurements lead to an approximate 0.2 km reduction in the 90% confidence interval upper boundary for neutron star radii, along with a notable decrease in Bayesian evidence, suggesting potential conflicts with prior data and/or the need for more adaptable models.

Over the last few years, researchers have become increasingly interested in understanding how dark matter affects neutron stars, helping them to better understand complex astrophysical phenomena. In this paper, we delve deeper into this problem by using advanced machine learning techniques to find potential connections between dark matter and various neutron star characteristics. We employ Random Forest classifiers to analyze neutron star (NS) properties and investigate whether these stars exhibit characteristics indicative of dark matter admixture. Our dataset includes 32,000 sequences of simulated NS properties, each described by mass, radius, and tidal deformability, inferred using recent observations and theoretical models. We explore a two-fluid model for the NS, incorporating separate equations of state for nucleonic and dark matter, with the latter considering a fermionic dark matter scenario. Our classifiers are trained and validated in a variety of feature sets, including the tidal deformability for various masses. The performance of these classifiers is rigorously assessed using confusion matrices, which reveal that NS with admixed dark matter can be identified with approximately 17% probability of misclassification as nuclear matter NS. In particular, we find that additional tidal deformability data do not significantly improve the precision of our predictions. This article also delves into the potential of specific NS properties as indicators of the presence of dark matter. Radius measurements, especially at extreme mass values, emerge as particularly promising features. The insights gained from our study are pivotal for guiding future observational strategies and enhancing the detection capabilities of dark matter in NS. This study is the first to show that the radii of neutron stars at 1.4 and 2.07 solar masses, measured using NICER data from pulsars PSR J0030+0451 and PSR J0740+6620, strongly suggest that the presence of dark matter in a neutron star is more likely than only hadronic composition.

For the first time, we use relativistic mean-field approximation with density-dependent couplings, adjusted by the Density-Dependent Meson-Exchange 2 (DDME2) parameterization, to investigate the effects of dark matter on supernova remnants. We calculate the nuclear equation of state for nuclear and dark matter separately, under the thermodynamic conditions related to the evolution of supernova remnants. A mirrored model is adopted for dark matter, and its effect on remnant matter is studied using a two-fluid scenario. At each stage of the remnant evolution, we assume that dark and ordinary matter have the same entropy and lepton fraction, and a fixed proportion of dark matter mass fraction is added to the stellar matter to observe its effects on some microscopic and macroscopic properties of the star. We observe that dark matter in the remnant core reduces the remnant’s maximum mass, radius, and tidal deformability. Moreover, dark matter heats the remnant matter and alters particle distributions, thereby decreasing its isospin asymmetry and increasing the sound speed through the matter.

We explore the influence of symmetry energy and the $\sigma$-cut potential on the properties of pure nucleonic and hyperon-rich neutron stars employing the relativistic mean-field (RMF) model with the S271 parameter set. The effects of symmetry energy are modulated by the ${\mathrm{\Lambda }}_v$ coupling, while the $\sigma$-cut potential is governed by the free parameter $f_s$. The coupling constants between hyperons and mesons are ascertained based on the most recent hyperon-nucleon potentials derived from existing experimental data. Our analysis suggests that ${\mathrm{\Lambda }}_v$ has more effect compared to $f_s$ on the composition and global properties of neutron stars. Our results are consistent with various observational data, particularly with the GW170817 data.